model with full system configuration and full integration is mandatory
for a valid performance test. Since DS0 and DS1 iterations can be done
quicker than with a full model, DS1 iterations should be made first, but
don’t wait too long to work with the full model. Several connectivity
or performance issues would be undetected in DS1 but would show up
in a full model. Just like with DS0 and DS1, it takes multiple iterations
of lengthy full-model builds before testing is complete.

Example of Large Model Problem

A problem was detected when one utility’s background objects were
being duplicated multiple times. Since background objects do not
affect connectivity, it wasn’t impactful enough to be noticed until the
full model was built. Once the utility began using the full model, the
quantity of background objects consumed too much system memory,
so the maps could not be displayed. Prior to the full model, the viewer
tool loaded slower than expected, but the data still displayed. With the
full model, failure to load messages appeared. Ordinarily, the amount
of data loading would be well within the limits, but because this limit
was hit immediately upon trying to load a single search result, a
definite data quantity problem was revealed. It took several weeks to
fix the problem because more than one fix attempt was required. A lot
of time was therefore used just waiting for builds to finish. This was
only one of several data issues found in the full model.

Coding Fixes and Workarounds

Temporary workarounds for bad data, while not ideal, are used “to getby” until a permanent fix is made. Sometimes there is insufficient timeto make the permanent fix before the go-live date. Other times, the fixis complex, touches many aspects and adds too much risk right beforethe go-live date. There is the risk that even if it’s believed the problemis solved, a new showstopper problem results from implementing thefix. Fixing one layer of problems can reveal additional problems inthe next layer. If continual attention was not given to the model fromearly on, the consequence is increased pressure to resolve all problemsimmediately, compact the schedule, and bare the risk of unresolvedissues on the go-live date. Fixing too much, too quickly, too radicallycan impact stability, user confidence, performance or go-live dates.

When deciding whether to fix or work around, ask:
• Is the workaround reasonable?

• Would fixing require altering a go-live date?

• Is the sponsor’s go-live deadline flexible?

• What is the level of risk involved in the fix (include testing time available)?

• Can the permanent fix be made in a timely manner?

Example of Connectivity Issues

Source data issues at one utility caused its ADMS model to have
many connectivity problems near circuit breakers. While best practice
would have been to cleanse the data in the source system, in this case
a difficult and complex update process made that impractical if the
utility was to make the planned go-live date. Instead, a work-around was
implemented involving jumpers placed to bypass problem areas. While
the workaround still took time to implement and delayed the go live, it
was completed in a more acceptable time and the delay to production
was minimized. Once it went live, the utility planned the permanent fix
and implemented the fix at a later time on their live system.

Conclusion

Perfect data is unattainable, but the higher the data quality, the greater
the systems’ value. It is important to aim high, but as Voltaire might
say; “Don’t let the perfect be the enemy of the good.” If you wait for
perfect data, you will never go live. Go live when the data is sufficient to
create business value, but don’t stop working to improve. Data quality
improvement and maintenance is a never-ending process. Begin data
reviews early, make wise use of limited business user’s time, improve
data where necessary and justified, and choose the appropriate data
model type and size. If you do this, you significantly increase your
likelihood of a successful ADMS project implementation.

mains and service lines along with other notable features, all with
relevant attributes attached.

After mapping one or more installs, the inspector need only
return to his truck, which has been equipped with WiFi capability. He
wirelessly uploads the collected data to the Questar Gas GIS in Salt
Lake City where it is immediately accessible to all other crews and
departments. Within a few days, a GIS technician in the engineering
department checks the GPS feature locations and attributes for
completeness. If all is approved, the job status is completed.

“From the GPS GIS, details of the job will notify various
departments the project is completed,” said Zesiger.

The work order management system, for example, receives details
of the installation including any additional tasks completed by the field
crews to calculate payment for the contractor. It notifies accounting
to cut the check and additional data is sent to other departments for
their use. More importantly, details of maintenance and repairs will be
permanently linked to every asset in the GIS database.

“As regulations tighten, this is the kind of information every gas
utility must be able to access,” said Vlass.

Benefits of Integrated Mapping

A benefit is that the entire GPS as-built is one mapping system; a user
no longer has to open up individual documents to look at mains and
services.

Giles believes the solution will pay off in two significant ways
as the assets age. First, integration with back-office applications will
enable Questar to provide government regulators with complete details
on the installation, maintenance and repair history of every asset in
the ground. Secondly, the improved spatial accuracy of the maps will
enable repair crews to find buried assets quickly when seconds count.

“The bottom line is that with mains and services, we have to beable to find that buried asset day or night for as long as that pipe in theground regardless of whether it has a 10-year or 100-year lifespan,”said Zesiger. “This system lets us do that.”The inspection department has begun introducing the as-builtmapping system to other personnel and other departments. The utilityis developing techniques to use it in mapping retirement of assets andbore hole workflows. The Questar team is exploring capabilities ofthe core system to expand into high pressure pipeline inspection.